초록

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Abstract ▼ AI-Helper

The goal of word sense disambiguation(WSD) is to determine which sense of an ambiguous word is invoked in a particular use of the word. It plays an important role in many natural language processing applications such as machine translation and information retrieval. This paper proposes a method for ...

The goal of word sense disambiguation(WSD) is to determine which sense of an ambiguous word is invoked in a particular use of the word. It plays an important role in many natural language processing applications such as machine translation and information retrieval. This paper proposes a method for automatic word sense disambiguation based on Korean WordNet. The basic assumption of this suggested method is that contextual words provide strong and consistent clues to the sense of an ambiguous word. Relevance between the ambiguous words and its contextual words is used to disambiguate the sense of the target word. In this paper, relevance between the ambiguous words and its contextual words is calculated by chi-square statistics. In tum, the chi-square between the ambiguous words and its contextual words is obtained from the related words of the target word in Korean WordNet and their co-occurrence extracted from a large unannotated corpus. A word sense having maximum chi-square with contextual words is selected as right sense in the given sentence. Ten ambiguous nouns have been disambiguated by the proposed method. The result of experiment shows that the model obtains 86.2% average accuracy.

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